Current methods for assessing voice quality in patients with voice disorders that rely solely on either auditory perception, or acoustic analysis, are inherently inadequate. There is a pressing need to develop a reliable and objective measure of voice quality can be is derived automatically from the acoustic signal, and at the same time is consistent with human perception. The primary aim of this project is to develop an improved (automated) method for objectively measuring the perceptually salient noise in the human voice that can be implemented on existing clinical instrumentation. The new method, named Automated Psychoacoustics-Based Voice-Quality Assessment (APVA), will be based on an innovative combination of well established principals of human psychoacoustics, and recent advances in signal compression technology. Phase I of this work will mainly involve the development and testing of algorithms for estimating a perceptually weighted signal-to-noise (SNR) voice quality measure for continuous speech. Phase II will be devoted to integrating the new method into existing computer voice evaluation systems, coupled with rigorous clinical development and testing. It is expected that the APVA method will lend new insights into the clinical manifestations of disordered voice production, and greatly improve the ability of clinicians to quantify and track the vocal status of voice patients for diagnostic and treatment purposes.